Duplicate from HumynLabs/Korean_Product_Labels_Image_Dataset

Co-authored-by: Humyn Labs <HumynLabs@users.noreply.huggingface.co>

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README.md

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+---
+license: cc-by-4.0
+pretty_name: 'Korean Product Labels Image Dataset'
+language:
+- ko
+tags:
+- image
+- korean
+- product-labels
+- packaging
+- text-recognition
+- ocr
+- ai-research
+- consumer-goods
+- computer-vision
+- retail
+- multilingual
+task_categories:
+- image-classification
+- text-recognition
+- product-detection
+size_categories:
+- 1K<n<10K
+---
+
+# Korean Product Labels Image Dataset
+*This dataset contains a diverse collection of high-resolution images of Korean product labels and packaging. The dataset spans categories such as food, cosmetics, beverages, and household items, designed to support OCR, product classification, and visual-language AI research.*
+
+## Contact
+For queries or collaborations related to this dataset, contact:  
+  - anoushka@kgen.io  
+  - abhishek.vadapalli@kgen.io  
+
+## Supported Tasks
+
+- **Task Categories**:  
+  - Image Classification  
+  - Text Recognition (OCR)  
+  - Product Detection  
+
+- **Supported Tasks**:  
+  - Text extraction from Korean product labels and packaging  
+  - Product category classification (food, cosmetics, household goods, etc.)  
+  - Brand and ingredient recognition  
+  - Multilingual OCR for bilingual (Korean-English) labels  
+  - Visual-language model training for retail and e-commerce AI applications  
+
+## Languages
+
+- **Primary Language**: Korean  
+- **Secondary Presence**: English (common in international or export products)  
+
+## Dataset Creation
+
+### Curation Rationale
+This dataset was curated to help AI systems understand visual and textual content on Korean product packaging. It supports the development of OCR, product recognition, and multilingual retail automation technologies for smart shopping, cataloging, and consumer research.
+
+### Source Data
+- **Contributors**: Field photographers and data collectors from retail stores, supermarkets, and e-commerce listings  
+- **Collection Process**: Product labels were photographed or extracted from publicly available catalog images. All images were manually reviewed to remove barcodes, serial numbers, or any sensitive identifiable information.  
+
+### Other Known Limitations
+- **Bias**: Certain product categories (e.g., food and cosmetics) are more represented than industrial goods  
+- **Lighting and Reflection**: Glossy packaging may introduce glare or partial occlusion in some images  
+- **Language Mix**: Some packaging includes mixed Korean-English or Korean-Chinese text which may affect OCR accuracy  
+
+## Intended Uses
+
+### ✅ Direct Use
+- Training OCR and product recognition models  
+- Multimodal research in retail and consumer goods AI  
+- Text understanding and translation in packaging contexts  
+- Visual search and product identification for e-commerce applications  
+
+### ❌ Out-of-Scope Use
+- Commercial replication or rebranding of existing product labels  
+- Extraction of proprietary design elements for commercial gain  
+- Any use that violates intellectual property or packaging rights  
+
+## License
+
+CC BY 4.0